Process Monitoring, Diagnosis and Control of Additive Manufacturing

doi:10.1109/TASE.2022.3215258

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 平行智能技术与系统团队

	Process Monitoring, Diagnosis and Control of Additive Manufacturing
	Fang, Qihang 1,2; Xiong, Gang1,3 ; Zhou, MengChu 4,5; Tamir, Tariku Sinshaw 1,2; Yan, Chao-Bo 6,7; Wu, Huaiyu1,3 ; Shen, Zhen1,3 ; Wang, Fei-Yue1,3
发表期刊	IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
ISSN	1545-5955
	2022-11-14
页码	27
通讯作者	Shen, Zhen(zhen.shen@ia.ac.cn)
摘要	Additive manufacturing (AM) can build up complex parts in a layer-by-layer manner, which is a kind of novel and flexible production technology. The special manufacturing capability of AM shows great application potential in various fields. However, an open-loop control method cannot guarantee the reliability and repeatability of an AM process. Defects often occur to deteriorate product quality and lead to material and time waste, which hinders the development of AM industry. In this regard, a lot of efforts have been made to make an AM process more controllable. This work proposes an AM control framework that divides the related studies into three feedback loops, including the in-situ monitoring of process defects, fault diagnosis of 3-D printers, and closed-loop control of an AM process. These three loops constitute the inspection and control of AM from the machine level to product level. Specifically, the measurement requirements for monitoring techniques, defect detection, fault diagnosis, and closed-loop control are summarized. The challenges and future trends in realizing a more reliable and repeatable AM process are discussed. Note to Practitioners-This survey is motivated by urgent need to solve product quality problems in additive manufacturing (AM) caused by open-loop control. Three feedback loops can be established to solve them. The first one is defect detection that inspects part quality during fabrication. The second one is the fault diagnosis of a 3-D printer that monitors the health and operation conditions of its actuators. The last one is closed-loop control that improves AM process reliability and repeatability by regulating process variables in real time. These three loops are all based on the feedback signals of in-situ monitoring systems. This paper reviews the related studies and provides guidance for establishing the monitoring systems, performing defect detection and fault diagnosis, and designing closed-loop control systems, which helps realize more reliable and repeatable AM.
关键词	Additive manufacturing (AM) in-situ monitoring defect detection fault diagnosis closed-loop control
DOI	10.1109/TASE.2022.3215258
关键词[WOS]	CONVOLUTIONAL NEURAL-NETWORK ; ITERATIVE LEARNING CONTROL ; LASER MELTING PROCESS ; IN-SITU MEASUREMENTS ; CLOSED-LOOP CONTROL ; FUSION AM PROCESS ; METAL-DEPOSITION ; DEFECT DETECTION ; FAULT-DIAGNOSIS ; QUALITY-CONTROL
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2018YFB1702700] ; National Natural Science Foundation of China[U1909204] ; National Natural Science Foundation of China[U1909218] ; Scientific Instrument Developing Project of the Chinese Academy of Sciences (CAS)[YZQT014] ; Guangdong Basic and Applied Basic Research Foundation[2021B1515140034] ; Foshan Science and Technology Innovation Team Project[2018IT100142] ; Youth Foundation of the State Key Laboratory for Management and Control of Complex Systems[Y6S9011F1G] ; Fundo para o Desenvolvimento das Ciencias e da Tecnologia (FDCT)[0047/2021/A1] ; CAS Science and Technology Service Network Initiative (STS) Dongguan Joint Project[20201600200072] ; CAS Key Technology Talent Program
项目资助者	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Scientific Instrument Developing Project of the Chinese Academy of Sciences (CAS) ; Guangdong Basic and Applied Basic Research Foundation ; Foshan Science and Technology Innovation Team Project ; Youth Foundation of the State Key Laboratory for Management and Control of Complex Systems ; Fundo para o Desenvolvimento das Ciencias e da Tecnologia (FDCT) ; CAS Science and Technology Service Network Initiative (STS) Dongguan Joint Project ; CAS Key Technology Talent Program
WOS研究方向	Automation & Control Systems
WOS类目	Automation & Control Systems
WOS记录号	WOS:000886928200001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：22[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/51255
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
通讯作者	Shen, Zhen
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing Engn Res Ctr Intelligent Syst & Technol, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Guangdong Engn Res Ctr 3D Printing & Intelligent M, Cloud Comp Ctr, Dongguan 523808, Peoples R China 4.New Jersey Inst Technol, Dept Elect & Comp Engn, Newark, NJ 07102 USA 5.Macau Univ Sci & Technol, Inst Syst Engn, Macau 999078, Peoples R China 6.Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian 710049, Shaanxi, Peoples R China 7.Xi An Jiao Tong Univ, Fac Elect & Informat Engn, Sch Automation Sci & Engn, Xian 710049, Shaanxi, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Fang, Qihang,Xiong, Gang,Zhou, MengChu,et al. Process Monitoring, Diagnosis and Control of Additive Manufacturing[J]. IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING,2022:27.
APA	Fang, Qihang.,Xiong, Gang.,Zhou, MengChu.,Tamir, Tariku Sinshaw.,Yan, Chao-Bo.,...&Wang, Fei-Yue.(2022).Process Monitoring, Diagnosis and Control of Additive Manufacturing.IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING,27.
MLA	Fang, Qihang,et al."Process Monitoring, Diagnosis and Control of Additive Manufacturing".IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2022):27.